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A Formal-Concept-Lattice Driven Approach for Skyline Refinement

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Advances and Trends in Artificial Intelligence. From Theory to Practice (IEA/AIE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11606))

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Abstract

Skyline queries constitute an appropriate tool that can help users to make intelligent decisions in the presence of multidimensional data when different, and often contradictory criteria are to be taken into account. Based on the concept of Pareto dominance, the skyline process extracts the most interesting (not dominated in sense of Pareto) objects from a set of data. However, this process often leads to a huge skyline, which is less informative for the end-users. In this paper, we propose an efficient approach to refine the skyline and reduce its size, using the principle of the formal concepts analysis. The basic idea is to build a formal concept lattice for skyline objects based on the minimal distance between each concept and the target concept. We show that the refined skyline is given by the concept that contains k objects (where k is a user-defined parameter) and has the minimal distance to the target concept. A set of experiments are conducted to demonstrate the effectiveness and efficiency of our approach.

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Author information

Authors and Affiliations

  1. DIF-FS/UMBB, Boumerdes, Algeria

    Mohamed Haddache

  2. LIAS/ENSMA, Poitiers, France

    Allel Hadjali

  3. LRIA/USTHB, Algers, Algeria

    Hamid Azzoune

Authors
  1. Mohamed Haddache
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  2. Allel Hadjali
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  3. Hamid Azzoune
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Corresponding authors

Correspondence to Mohamed Haddache , Allel Hadjali or Hamid Azzoune .

Editor information

Editors and Affiliations

  1. Institute for Software Technology, Graz University of Technology, Graz, Austria

    Franz Wotawa

  2. Department of Applied Informatics, University of Klagenfurt, Klagenfurt, Austria

    Gerhard Friedrich

  3. Institute for Software Technology, Graz University of Technology, Graz, Austria

    Ingo Pill

  4. Institute for Software Technology, Graz University of Technology, Graz, Austria

    Roxane Koitz-Hristov

  5. Department of Computer Science, Texas State University, San Marcos, TX, USA

    Moonis Ali

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Haddache, M., Hadjali, A., Azzoune, H. (2019). A Formal-Concept-Lattice Driven Approach for Skyline Refinement. In: Wotawa, F., Friedrich, G., Pill, I., Koitz-Hristov, R., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2019. Lecture Notes in Computer Science(), vol 11606. Springer, Cham. https://doi.org/10.1007/978-3-030-22999-3_47

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  • DOI: https://doi.org/10.1007/978-3-030-22999-3_47

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  • Print ISBN: 978-3-030-22998-6

  • Online ISBN: 978-3-030-22999-3

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